Your Buyers Asked ChatGPT About You. Here Is What It Said.
We ran a fixed set of 40 buying-intent prompts across ChatGPT, Perplexity, Gemini, and Claude for a range of B2B brands. Most were invisible. The rest were misrepresented. Here is the pattern — and what to do about it.
A simple exercise reveals the problem faster than any deck: take the 40 questions a company's buyers most plausibly ask an AI assistant — 'best platforms for X', 'how should we evaluate Y', 'alternatives to Z' — and run them across the four major LLMs. The results follow a pattern that surprises almost every leadership team.
The three outcomes
Most brands simply do not appear. Not on the shortlist, not in the comparison, not even as an 'also consider'. A smaller share appear but are characterised inaccurately — positioned in the wrong category, credited with a competitor's weaknesses, or described using messaging from two rebrands ago. Only a minority are present and represented correctly.
Why this happens
LLMs form opinions from the public record: third-party mentions, review sites, community threads, analyst coverage, and the consistency of your own narrative across the web. If that record is thin, stale, or contradictory, the model fills the gap with whatever is available — usually your loudest competitor's framing.
What to do this quarter
Start by measuring. Establish your citation rate across a fixed prompt set and track it monthly, the way you track branded search. Then close the gaps in order of leverage: correct your structured data, refresh the third-party sources models cite most, and publish authoritative content that answers category questions directly. Visibility compounds — but only after you can see it.
Want this applied to your revenue system?
The Revenue Diagnostic gives you a clear picture of your AI visibility and growth gaps in 4–6 weeks.